How Google does Machine Learning

How Google does Machine Learning

This course is part of multiple programs.

Instructor: Google Cloud Training

What you'll learn

Describe Vertex AI Platform and how it's used to quickly build, train, and deploy AutoML machine learning models without writing any code
Describe best practices for implementing machine learning on Google Cloud
Leverage Google Cloud tools and environment to do ML
Articulate Responsible AI best practices

Skills you'll gain

Details to know

Shareable certificate

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Assessments

5 assignments

Taught in English

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This course is available as part of

When you enroll in this course, you'll also be asked to select a specific program.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

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There are 6 modules in this course

This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models.

This module introduces the course series and the Google experts who will be teaching it.

What's included

2 videos

In this module, you explore building a data strategy around machine learning.

What's included

7 videos2 readings1 assignment

7 videosTotal 34 minutes

Introduction0 minutesPreview module
What is ML?8 minutes
What problems can it solve?6 minutes
Activity intro: Framing a machine learning problem1 minute
Activity solutions: Framing a machine learning problem4 minutes
Infuse your apps with ML3 minutes
Build a data strategy around ML10 minutes

2 readingsTotal 40 minutes

Activity: Framing a machine learning problem30 minutes
Resources: What It Means to Be AI First10 minutes

1 assignmentTotal 10 minutes

What it Means to be AI First10 minutes

This module shares the organizational know-how Google has acquired over the years.

What's included

7 videos1 reading1 assignment

All machine learning starts with some type of goal - whether it be a business use case, academic use case, or goal you are trying to solve. This module reviews the process of determining whether the model is ready for production the “proof of concept” or “experimentation” phase.